Google Announces On Wider Skin Tone Range For Better Artificial Intelligence Recognition

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June 24, 2021

Google announces that it would be developing new methods to come up with a wider skin tone range, leaving the age-old scale behind to ensure that the artificial intelligence products produced are not being biased to any skin tone.

The current tool that Google is using or, for that matter, any skin tone detection system uses is the Fitzpatrick skin type scale (FST). This scale has six skin tones ranging from pale to dark brown/black skin. It was introduced in 1970 for dermatology purposes, and all the tech companies rely on it for facial recognition and smartwatch pulse detection.

Last October, during the federal technology conference, it was recommended to abandon FST due to its poor range of color representation for facial recognition. In response to this, Google took a step forward in developing a new method for skin tone recognition.

Google recognized that the forthcoming products will be assisted with robust artificial intelligence, hence will be much more sensitive to skin tones and that having the same FST scale would lead to poor performance of the products for darker and yellow skin tones. To curb racism and for the products to be highly accessible the company leaped ahead of its other competitive peers.

Artificial intelligence systems are more sensitive to skin tones and a scale with a minimum range like FST would not do the job perfectly. It was proved when Facebook was testing their AI systems for deepfake recognition in April. The researchers said that FST does not encircle the diversity in skin tones. It failed to recognize a few of the skin tones between white and brown.

A study conducted by University of California San Diego clinicians shows that FST often fuels false assurances about heart rates on smartwatches for darker skin tones. For the advanced artificial intelligence to not be discriminated against anyone, there at least need to be 12-18 tones rather than six shades, says Victor Casale, a colour expert.

Candy Shop Slaughter: A Video Game Created By GPT-3

By

Manisha Kalagara

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June 24, 2021

Candy shop slaughter is a video game that was developed using GPT-3 by Fractl gaming group for OnlineRoulette.com. It is a full-fledged game that consists of all the elements required for a successful mobile game.

Artificial intelligence is being expanded to various levels in every domain each day, even in the gaming industry. Although there are many AI and VR games, this is the first game designed entirely by artificial intelligence. The game is based on the main character named Freddy Skittle and has two modes. In the story mode, the player can accumulate points by performing various activities. The game turns into a 3D fighter game in arcade mode, wherein the blood and guts are transmuted into candies and treats. Not only that, but the game consists of 12 other additional characters that are bosses and companion players, all created by AI.

The artificial intelligence model GPT-3 was used to fabricate the game, an OpenAI language model that can not only generate human-like text using pre-trained algorithms but also generate code. The model was designed to create anything that requires a language structure, i.e., from answering questions to writing essays, translating and summarizing texts. In fact, Fractl had made a complete website that entirely had blog content using GPT-2 and GPT-3.

Playing around with the same technique, the gaming enterprise had created all the game characters, game art, and gameplay using GPT-3. Joe Mercurio, the creative strategy lead of Fractl, came up with the idea and development of the project while Tynski, the cofounder, developed the AI outputs.

OnlineRoulette had surveyed 1000 gamers to find out how they found the game to be along with its various aspects and if they were willing to pay for an AI-generated game. The survey found that 10% of the gamers found it unoriginal and 54% found Candy Shop Slaughter to be original, and a shocking 20% considered it very authentic. In addition, 67% of them ranked it as high quality, and 65% were willing to pay for it.

The Pentagon will launch an Artificial Intelligence and Data Accelerator Initiative

By

Dipayan Mitra

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June 24, 2021

The Pentagon Launched Initiative For Artificial Intelligence

The Pentagon, on Tuesday, announced that it aims to develop combatant command networks for the data-heavy, artificial intelligence-powered reality of the future battlefield.

Kathleen Hicks, Deputy Secretary of Defence, said that the artificial intelligence initiative is an effort that will deploy technical teams to combat commands to train military networks for Joint All-Domain Command and Control.

The Pentagon plans to quickly pass the best data from artificial intelligence-backed systems to army personnel. He also said, “Its goal is to rapidly advance data and AI-dependent concepts like Joint All-Domain Command Control.”

This initiative will depend upon the combatant commands’ experimentation events and exercises to test artificial intelligence capabilities. The implementation of this concept would require an advanced artificial intelligence system to process data on a battlefield.

This AIDA initiative would create foundational capabilities through numerous exercises to continuously gain knowledge, said Hicks. The Department of Defence is creating operational data teams that will be dispatched to eleven combatant commands.

The teams will meticulously work, manage, catalog, and automate data feeds that inform decision-making. They will ensure that the data is captured and remains usable until it is used to create decision advantages on the ground. DOD will also strengthen data relationships with additional “flyaway teams of technical experts” to help soldiers streamline and automate workflows by integrating artificial intelligence.

It will also use the gathered data to update network infrastructure and the effectiveness of its global warfighting capabilities. DOD plans to understand and analyze the issues that impair their current artificial intelligence capabilities through successive experiments.

Hicks also said, “This will produce data and operational platforms designed for real-time sensor-data fusion, automated command and control tasking, and autonomous system integration. It will allow data to flow across both geographic and functional commands.”

At a different event, Lt. Gen. Dennis Crall said that the Pentagon had started an analysis to understand the technology gaps it needs to overcome to prepare for wars in the future.

HPE Acquired Artificial Intelligence Startup Determined AI

By

Dipayan Mitra

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June 23, 2021

Hewlett Packard Enterprise (HPE) recently announced it has acquired an artificial intelligence startup Determined AI. The company said that the reason for this acquisition is to train artificial intelligence models faster utilizing Determined AI’s open-source machine learning (ML) platform.

The company plans to combine the startup’s artificial intelligence platform with its own high-performance computing platform to reduce the production time of artificial intelligence-powered products for better and quicker customer service.

Determined AI was founded in 2017 by Evan Sparks, Neil Conway, and Ameet Talwalkar in San Francisco. The company quickly became popular in the industry after the launch of its open-source artificial intelligence platform in 2020. Their platform has been used in several different industries like autonomous vehicles, defense contracting, biopharmaceuticals, and manufacturing.

Senior Vice President of HPE, Justin Hotard, said, “Determined AI’s unique open-source platform allows ML engineers to build models faster and deliver business value sooner without having to worry about the underlying infrastructure.” He further mentioned that as the world enters the age of insights, the customers have highlighted the requirement of machine learning to provide faster answers from their data.

The company’s primary motive is to leverage artificial intelligence training to launch projects which require specialized computing skills. HPE and Determined AI’s team plans to make high performance computing more accessible with its GreenLake edge to cloud service.

Determined AI’s unique artificial intelligence platform enables researchers to innovate and boost their delivery time by eliminating the complexity and cost related issues with machine learning development.

Determined AI’s CEO, Evan Sparks, said, “Over the last several years, building AI applications have become extremely compute, data, and communication intensive.” He also added that the acquisition would help accelerate their speed to create artificial intelligence applications and will also expand their customer reach.

NVIDIA Partners With Equinix To Launch Its Artificial Intelligence Launchpad

By

Dipayan Mitra

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June 23, 2021

NVIDIA Partners With Equinix To Launch Its Artificial Intelligence Launchpad

NVIDIA recently announced its partnership with Equinix to launch its artificial intelligence launchpad to expand its artificial intelligence hardware from the clouds, where the hyper-scalers control the hardware designs. This decision was made to co-locate data centers that are cloud-based but allow users to buy and install NVIDIA DGX servers and have them hosted and managed by a third party, and if need be, with cloud-based pricing on bare metal instances.

The company has released its Base Command software as a part of its complete artificial intelligence stack with which NVIDIA can run its machine learning training in its supercomputers.

Companies worldwide are planning to develop in the cloud and deploy within data centers that lower cost, data security, and workload isolation. The process of building infrastructure is a significant concern for enterprises and is highly time-consuming.

Original Equipment Manufacturers (OEMs) worldwide are trying to convert all of their hardware into the cloud in terms of how it is consumed while also making it a physical asset that customers can control either on-premises or in co-location facilities.

General Manager of NVIDIA, Justin Boitano, said, “So instead of in our engagements where enterprises say, ‘I need to go buy servers so I will come back in two or three months to get started,’ they can get started instantly.” He further added that with the help of this, companies could assemble their infrastructure in a jiffy rather than building their own setup from scratch.

“This is going to aid customers to get started on this journey faster and show value to internal stakeholders before making bigger CAPEX investments – and help accelerate the entire cycle for us,” said Boitano.

Equinix will start providing this artificial intelligence launchpad in the summer of 2021 in the United States. Initially, the focus will be on the locations having enterprises willing to work on artificial intelligence and then roll out globally.

Frontier Development Lab To Use Artificial Intelligence In Space Science Explorations

By

Dipayan Mitra

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June 23, 2021

Frontier Development Lab To Use Artificial Intelligence In Space Science Explorations

Frontier Development Lab has built a team of researchers who will use artificial intelligence and machine learning to explore space science. FDL plans to use artificial intelligence to solve challenges that scientists face in lunar resources, astronaut health, and earth science.

Frontier Development Lab is a public-private partnership with NASA in the USA and ESA in Europe. It brings together industry leaders in space science and artificial intelligence like Google Cloud, Luxembourg Space Agency, Microsoft, Intel, Lockheed Martin, and many more.

Hosted by NASA Ames Research Center and the SETI Institute, the FDL aims to combine physics and machine learning to help explore several issues in space science and humanity.

Bill Diamond, the president and CEO of the SETI Institute, said, “In an impressive pivot, our 2020 FDL participants demonstrated that interdisciplinary researchers could achieve extraordinary results in an intense sprint environment and do it virtually, across about nine time zones.”

He also clarified that the FDL artificial intelligence and machine learning accelerator event would again be organized virtually in 2021. FDL was founded in 2016, after which it has successfully exhibited the potential for interdisciplinary artificial intelligence approaches to overcome challenges in lunar prospecting, planetary defense, and space weather.

The lab handles knowledge gaps in space science, using machine learning experts with researchers in astronomy, astrophysics, and planetary science. They research together for a period of eight weeks during the summer break of the academic year. The researchers of FDL have already used artificial intelligence to predict solar activities, generate 3D models of potentially dangerous asteroids, and map lunar resources.

FDL 6.0 will build upon the work, processes, and learning developed over the last five years, with the potential to deepen the impact of the work and advance science in new ways.

Deep Learning For AI: A Paper By The Experts

By

Manisha Kalagara

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June 23, 2021

A Paper By Yoshua Bengio, Yen LeCun, & Geoffery Hinton

The three scholars of artificial intelligence and deep learning, Yoshua Bengio, Yann LeCun, and Geoffery Hinton, announced that their paper Deep Learning For AI would be published officially in July 2021. The paper would be regarding neural networking, artificial intelligence and deep learning.

In 2018, the three researchers dug deep into how simple neural networks can learn a rich internal representation required to perform complex tasks such as recognizing objects or understanding language. The three explored the field to its maximum capacity and have put forth their thoughts and learnings in the paper, Deep Learning of AI.

Deep learning systems are doing well in the present for system 1 type that includes object recognition and understanding language. But not so well for system 2 tasks such as learning with little or no external supervision, using deep learning to perform tasks that humans and animals do by using a deliberate sequence of steps, and coping with test examples that arrive from a different distribution than the training examples. The paper describes a few ways which can make deep learning systems perform well with system 2 tasks. Not only that, the paper also briefs about the origins and recent advancements in deep learning and AI.

The paper has three major purposes: trying to point to the direction in actual progress of AI and making them learn like humans and animals, by getting machines to understand the reasoning and getting machines perceived more robustly and work precisely like humans and animals.

The paper also engages with how many believe that there are problems that neural networks cannot solve and they tend to resort back to the classical AI symbolic approach, but this work suggests otherwise, that those goals can be achieved by making the neural networks more structured via extending the network itself.

“Deep learning has a great future; it is only going to get bigger and better, but there is still a long way to go in terms of understanding how to make neural networks effective, and we expect to have many more ideas,” said Geoffery Hinton in a video describing the paper.

Yellow Messenger Renamed To Yellow.ai To Launch Artificial Intelligence Powered Voice Bots

By

Dipayan Mitra

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June 23, 2021

Yellow messenger recently renamed itself Yellow.ai after the announcement of the launch of a new product suite. This change aims to prioritize the delivery of ‘Total Customer Experience (CX) Automation.’

The company launched artificial intelligence-powered voice bots to its existing platform of automated chat solutions. Yellow.ai’s new technology offers the best artificial intelligence and human intelligence to deliver precise and enhanced customer experience at a very competitive price bracket.

The company has already partnered with 700+ brands globally to provide them with Conversational CX automation service. This technology has now enabled brands to elevate the customer experience across multiple platforms Telephony, Google Assistant, Alexa, Instagram, Apple Business Chat, Web, WhatsApp, Facebook, Google Business Messages, Telegram, WeChat, LINE, and many more in 100+ languages.

Customers can now get personalized and unified assistance from the brands when they reach out to them via WhatsApp, web, or dialing the company’s customer service number. Some of the main features of Yellow.ai’s service include Multichannel voice experience via all the popular voice assistants, Text-to-Speech (TTS) capabilities which support numerous emotions like happiness and anger.

The platform also has a built-in personalization engine that can analyze the intent and sentiment of the customer, along with a continuous learning Speech-to-text (STT) system that will improve its accuracy over time. The platform offers an inclusive and unbiased approach to CX in every market segment.

The co-founder and CEO of Yellow.ai, Raghu Ravinutala, said, “The post-pandemic world is moving towards touchless UI, and ‘voice’ is playing a key role in enabling smarter brand-to-consumer engagement.” He added that Yellow.ai is dedicated to enabling human-like, engaging conversations with their new conversational CX platform.

Yellow.ai is hosting a global event, ‘Envision – the future of Voice AI’ on 22nd June to mark its product launch. The event will host industry leaders from Microsoft, Teleperformance, Concentrix, and many more.

Deutsche Bank Releases Paper On The Usage Of AI In Security Services

By

Manisha Kalagara

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June 23, 2021

On Saturday, Deutsche Bank released a paper titled “Unleashing the potential of AI in securities services,” which gives an insight on the potential usage of artificial intelligence and machine learning in security services and post-trade custody by banks.

This globally leading investment bank is no new to the game of AI; they have used AI earlier for advanced client segmentation processes along with their S-2 Predict tool to prevent settlement failures. And also as self-executing bots for natural-language messaging as part of their client-facing chatbot for customer assistance. Now they have pushed the usage of AI technology for risk management and for better understanding of client activities.

AI comes into play in risk management during the management of various risks that occur due to time-zone differences, imperfect communication across various sectors/chains, involvement of multiple clients, and also the hectic time pressure that comes while settling a trade. Tackling these risks using AI and ML gives both the banks and the clients a notable competitive advantage.

Deutsche Bank also mentioned in the paper that AI can be applied to the existing data to identify the current and real-time trends by using historical trends or identifying future trends by mixing past and present data. It can be used in client segregation, i.e. by dividing clients with similarities into various groups. This process will help the custodians develop better products and services that will meet the client’s shared and individual needs. Not only that, but AI can also assist and speed up the decision-making process by analysing all the data and trends in no time.

The paper gives insight into the various AI uses along with learning types, algorithm types, governance (to ensure model accuracy and consistency) and a list of key recommendations. The paper also specifies the benefits due to the usage of AI and ML in banks that includes: improving speed, efficiency, settlement lifecycle, and also open up new employment opportunities.

“The opportunities are endless, and we are not even yet scratching the surface. Going forward, we will continue pushing this emerging technology to the forefront – stay tuned!” mentioned Paul Maley, global head of securities of Duestch bank in the paper.

US Partners With India For Research In Artificial Intelligence For Mutual Benefits

By

Dipayan Mitra

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June 23, 2021

US partners with India for artificial intelligence

The United States and India have joined hands again by launching the U.S.-India Synthetic Intelligence (USIAI) Partnership. India’s massive potential in the field of artificial intelligence is the main reason for this partnership between the two democracies.

Joe Biden recently established the National Artificial Intelligence Initiative Office with the sole focus on partnering with the allies of the country for research and development of artificial intelligence. This partnership will be beneficial for both the countries, as India would get better chances to upgrade its infrastructures, and the US will get access to Indian tech talents.

Georgetown University’s Center for Security and Emerging Technology report mentioned that India produces seven times as many engineering graduates each year than the United States. But the lack of opportunities in the field of artificial intelligence retards India’s development.

11% of the top 50 artificial intelligence startups in the US are founded by Indian immigrants. Their contribution not only adds to the US economy but also benefits India through tech transfers, investment opportunities, and outsourcing.

Policymakers in India and the United States can facilitate their artificial intelligence ambitions by strengthening ties with Indian talents and backing their ventures in both nations. India’s colossal population produces way more graduates each year than its economy can absorb. This gives America the opportunity to lure talented individuals to the country.

This partnership can help India to encourage the US to set up University campuses in India, which would improve the standard of education. The increasing Indian tech diaspora in the US is a crucial element of the India-US artificial intelligence partnership that will enable the two countries to strengthen one another further and together implement emerging technologies in accordance with democratic values and principles.